Project Summary Alzheimer?s disease (AD) is the most common form of senile dementia and the sixth leading cause of death in the US. The failure of prior drug trials aimed at slowing the progression of AD has led to an increasing effort to study AD in its prodromal stages, when brain tissue damage is still minimal and drug therapy is more likely to be effective. However, assessing and monitoring early stage AD is challenging, and there is a pressing need for improved biomarkers that can help to evaluate the efficacy of new treatments. Diffusion MRI is a widely available, noninvasive approach for detecting subtle microstructural changes associated with early detection and disease progression, which can be of particular value in monitoring the effect on brain microstructure of AD medications being tested in drug trials. Recently, preliminary data from our group and others have demonstrated that advanced diffusion MRI methods, such as diffusional kurtosis imaging (DKI) and diffusion spectrum imaging, which both provide more information than standard diffusion tensor imaging, can substantially increase the sensitivity to detect brain microstructural alterations. Indeed, when applied to AD pathology, an approach developed by our group (DKI-based white matter modeling) was able to differentiate normal controls from amnestic mild cognitive impairment subjects. Although our results support the potential of DKI together with associated tissue modeling methods to provide imaging biomarker candidates for the neuropathological processes in AD, they have yet to be validated in a controlled animal model. To our knowledge, there are no previous studies that have systematically employed advanced diffusion MRI with an animal model to investigate the progression of AD from its earliest stages. The overall goal of this project is to validate and further develop advanced diffusion MRI methods for detecting the microstructural changes that accompany AD by using an established murine model of AD pathology. We will use 3xTg-AD mice, which exhibit both plaques and tangles, the hallmarks of AD pathology. In Aim 1, we will determine the time course of DKI-based metrics during the progression of AD. In Aim 2, we will establish connections between the diffusion metrics and histology in order to increase the biological interpretability of our DKI results. Finally, in Aim 3, we will explore the application to AD of an extended version of DKI, known as double pulsed DKI, aiming to determine whether this novel information can further increase the sensitivity to microstructural tissue changes. The successful completion of this research will demonstrate the viability of DKI-based metrics as neuroimaging biomarkers for monitoring AD progression and help to identify which specific metrics are most promising for the assessment of early stage AD. Such noninvasive imaging biomarkers are potentially of great value in aiding the development of new pharmacological therapies to treat this devastating disease.